[1]王桂林.城市化背景下中国PM2.5时空变化特征[J].山地学报,2024,(6):880-894.[doi:10.16089/j.cnki.1008-2786.000869]
　WANG Guilin.Spatiotemporal Evolution of PM2.5 Pollution in the Urbanizating Cities of China[J].Mountain Research,2024,(6):880-894.[doi:10.16089/j.cnki.1008-2786.000869]
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城市化背景下中国PM2.5时空变化特征
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2024年第6期
页码:
880-894
栏目:
山区发展
出版日期:
2024-12-20

文章信息/Info

Title:
Spatiotemporal Evolution of PM2.5 Pollution in the Urbanizating Cities of China
文章编号:
1008-2786-(2024)6-880-15
作者:
王桂林
(上海城建职业学院 城市发展研究中心,上海200438)
Author(s):
WANG Guilin
(Urban Development Research Center, Shanghai Urban Construction Vocational College, Shanghai 200438, China)
关键词:
城市化;  PM2.5污染;  MODIS;  GTWR
Keywords:
urbanization;  PM2.5 pollution;  MODIS;  GTWR
分类号:
X8
DOI:
10.16089/j.cnki.1008-2786.000869
文献标志码:
A
摘要:
快速城市化进程中,人类活动是城市PM2.5污染的主要因素。分析城市化对PM2.5污染的影响,掌握PM2.5污染演变规律,对于控制PM2.5污染,提升城市治理水平具有现实意义。然而,以往城市PM2.5污染研究多依赖地面监测点PM2.5数据,且未能有效排除PM2.5中自然源(如扬尘、海盐等)对城市污染的独立影响,从而在一定程度上影响了研究结果的准确性和可靠性。本研究基于卫星遥感气溶胶垂直厚度、 GEOS-Chem模拟值以及地面监测值,通过运用时空地理加权回归模型GTWR,反演了1998—2017年中国PM2.5污染和人为排放PM2.5(排除扬尘、海盐影响)的时空分布,并分析二者的演化关系。结果表明:(1)基于GTWR的PM2.5模拟精度为87.94%,比GEOS-Chem模型模拟精度高7.80%。(2)中国PM2.5污染空间分布呈倒“T”形态,纵横交界处华北平原污染最为严重; 人为排放PM2.5呈“胡焕庸线”分布格局,虽整体上升但具有阶段性波动趋势。(3)中国人口城市化水平与人为排放PM2.5污染呈显著正相关(R=0.66)。低城市化(人口城市化率为0～40%)城市的PM2.5污染处于最低水平; 中城市化(40%～60%)的PM2.5平均质量浓度为(27.49±8.95)μg?m-3,是低城市化的5.92倍; 高城市化(60%～80%)的PM2.5质量浓度均值为(34.40±7.71)μg?m-3,比中城市化城市高出25.14%,是低城市化的7.41倍; 北京、上海、天津的人口城市化率最高,处于80%～100%,PM2.5平均质量浓度为(61.60±10.15)μg?m-3,比高城市化城市高出79.07%,是中城市化城市的2.24倍,是低城市化城市的13.28倍。本研究结果可为改善城市空气质量、制定科学合理的污染防治策略提供相关依据。
Abstract:
In the process of rapid urbanization, human activities are the primary contributors to urban PM2.5 pollution. Analyzing the impact of urbanization on PM2.5 pollution and mastering the evolution law of PM2.5 pollution are of practical significance for removing PM2.5 pollution and improving the level of urban governance. Previous studies on urban PM2.5 pollution depended on ground-based PM2.5 data collected at ground monitoring stations in cities, and the influence of natural sources of PM2.5(such as fugitive dust and sea salt)on urban pollution were not effectively excluded, thereby affecting the accuracy and reliability of the research results to a certain extent.
In this study, based on aerosol optical depth(AOD)from satellite remote sensing, Goddard Earth Observation System Chemical(GEOS-Chem)model simulations, and ground-based monitoring data, it employed a Geographically Time Weighted Regression(GTWR)model to retrieve the spatiotemporal distribution of PM2.5 pollution and anthropogenic PM2.5 emissions(excluding the influence of fugitive dust and sea salt)in China from 1998 to 2017 and analyzed the evolutionary relationship between the two.
(1)The simulation accuracy of urban PM2.5 based on GTWR was 87.94%, which was 7.80% higher than that the simulation accuracy of GEOS-Chem model.
(2)In China, the spatial pattern of PM2.5 pollution showed an inverted “T” shape, with the North China Plain at the intersection being the most polluted. Anthropogenic PM2.5 emissions followed the “Hu Huanyong line” distribution pattern, showing an overall increase and a periodic fluctuation trend.
(3)There was a significant positive correlation(R=0.66)between the urbanization level of China's population and anthropogenic PM2.5 pollution.
(4)Cities with low urbanization(population urbanization rate of 0-40% )had the lowest PM2.5 pollution levels. The average PM2.5 concentration in moderately urbanized cities was 27.49±8.95 μg·m-3 which was 5.92 times that of low-urbanized cities.
(5)The average PM2.5 concentration in highly urbanized cities was 34.40±7.71 μg·m-3, which was 25.14% higher than that of medium-urbanized cities, and 7.41 times higher than that of low-urbanized cities. Beijing, Shanghai and Tianjin has the highest population urbanization rate, ranging from 80% to 100%, with an average PM2.5 concentration of 61.60±10.15 μg·m-3, which was 79.07% higher than that in highly urbanized cities, 2.24 times higher than that of medium-urbanized cities, and 13.28 times higher than that of low-urbanized cities.
Conclusively, urbanization pattern in China had a significant impact on PM2.5 pollution. The higher the level of urbanization, the more severe anthropogenic PM2.5 pollution is. The findings of this study can provide a scientific basis for improving urban air quality and formulating scientific and reasonable pollution prevention strategies.

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备注/Memo

备注/Memo:
收稿日期(Received date): 2023-12-23; 改回日期(Accepted date):2024-12-11
基金项目(Foundation item): 上海城建职业学院校级重点项目(cjky202541)。[ Key Project of Shanghai Urban Construction Vocational College(cjky202541)]
作者简介(Biography): 王桂林(1986-),女,江西上饶人,博士,副研究员,主要研究方向:大气污染。[WANG Guilin(1986-), female, born in Shangrao, Jiangxi Province, Ph.D., associate professor, specialized in air pollution] E-mail: kawgl@126.com
更新日期/Last Update: 2024-11-30